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. 2022 Jun 29;7(27):22997–23008. doi: 10.1021/acsomega.2c01395

Impact of Agroclimatic Variables on Proteogenomics in Sugar Cane (Saccharum spp.) Plant Productivity

Krishan K Verma †, Xiu-Peng Song †,*, Garima Yadav ‡, Hewan Demissie Degu §, Aqsa Parvaiz ∥, Munna Singh ‡, Hai-Rong Huang †, Ghulam Mustafa ∥, Lin Xu †, Yang-Rui Li †,*
PMCID: PMC9280927  PMID: 35847309

Abstract

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Sugar cane (Saccharum spp. hybrids) is a major crop for sugar and renewable bioenergy worldwide, grown in arid and semiarid regions. China, the world’s fourth-largest sugar producer after Brazil, India, and the European Union, all share ∼80% of the global production, and the remaining ∼20% of sugar comes from sugar beets, mostly grown in the temperate regions of the Northern Hemisphere, also used as a raw material in production of bioethanol for renewable energy. In view of carboxylation strategies, sugar cane qualifies as one of the best C4 crop. It has dual CO2 concentrating mechanisms located in its unique Krantz anatomy, having dimorphic chloroplasts located in mesophylls and bundle sheath cells for integrated operation of C4 and C3 carbon fixation cycles, regulated by enzymes to upgrade/sustain an ability for improved carbon assimilation to acquire an optimum carbon economy by producing enhanced plant biomass along with sugar yield under elevated temperature and strong irradiance with improved water-use efficiency. These superior intrinsic physiological carbon metabolisms encouraged us to reveal and recollect the facts for moving ahead with the molecular approaches to reveal the expression of proteogenomics linked with plant productivity under abiotic stress during its cultivation in specific agrizones globally.

1. Introduction

Water and land resources for agriculture may become limited globally in the near future1 because of the ever-increasing human population, requiring production of adequate food,2−4 which can be affected by environmental stress5 that impairs food production. The anticipated depletion and, most significantly, the harmful effects of atmospheric variables on nonrenewable fossil fuels necessitate the utilization of alternative energy sources. Biofuels are becoming an essential part of transportation fuel around the world, and they are produced through processes that discharge significantly lower pollutants.6,7 Hence, ecological understanding of regulating proteogenomics seems to be an urgent need for sustainable production of major crops, including sugar cane with improved productivity under adverse environmental conditions. The 2030 Agenda for Sustainable Development, adopted by the United Nations General Assembly in 2015, has developed 17 sustainable development goals for the world.8 The Food and Agriculture Organization (FAO) also set out 20 sustainable plans for the world.1 This agenda focuses on sustainable access and use of biodiversity. However, research shows that intense agriculture and habitat destruction are the reasons for the biodiversity reduction in the world due to the onset of environmental stress, which is considered the big problem of yield reduction globally.7,9−13 During stress, tolerant plants change their expression of genes to balance normal cellular and metabolic activities.14

Plant biomass accumulation is positively associated with the production and use of metabolites during the diurnal variation in photosynthetically healthy leaves for the biogenesis of carbohydrates which maintains/balances growth, development, and metabolic activities.15,16 The importance of sugar cane for the sugar and green bioenergy sectors, various techniques based on the photosynthetic capacity, and molecular changes has been proposed to enhance further cane productivity.16,17 The genus Saccharum contains over 38 species of perennial plants18 in western, central, and eastern flora from southern America, central Asia, East Asia, Africa, and Australia, with the presence of fibrous stalks enriched with sugar.19−21

Sugar cane is a major source of global sugar, accounting for about 80% of the production of world sugar;22 it is also effective for bioethanol production, and almost 50% of cane is used to generate ethanol.23,24 Recently established sugar cane cultivars have a diverse genome, more polyploidy and aneuploidy, around 70–80% of the Saccharum officinarum genome composition and 10–20% of Saccharum spontaneum, combining S. officinarum with higher sugar content ability with S. spontaneum hardiness, pathogenic tolerance, and rationing.25,26 Improving sugar cane traditional breeding programs is more difficult due to narrow genetic pools and a complex genome.27 Plant breeders have focused on the important agronomic traits of sugar cane, such as leaf gas exchange, yield, stalk number, stalk height, disease resistance, abiotic stress tolerance, sugar yield, total internode number, cane girth, cane weight, fiber content, tiller rate, number of productive tillers, pith, and growth ring shape to achieve the best combination of traits for satisfying farmers’ and consumers’ demands.18,21,28−30

Next-generation sequencing (NGS) technology has accelerated the genome sequencing and resequencing of polyploidy crops to determine molecular markers’ genetic and physical mapping in specific loci/genes. These identified markers may be used to conduct molecular marker-assisted selection (MAS) breeding or evaluate the genetic links between different accessions using genotyping technologies to improve agronomic traits.31−33 The evolution of transcriptome sequences has improved gene interpretation by providing insight into the domestication and control of gene function networks via gene expression and sequence patterns19,34−39 for modern breeding and genome editing.

A number of researchers involved in molecular techniques have been assessed in sugar cane crop production, i.e., transcriptomics and proteomics for enhancing crop production, sucrose content, and stress resistance mechanisms with molecular adaptations and mechanisms of sugar cane sensitivity for plant growth, development, and productivity.40,41 Transcriptomic techniques could be used to classify genes as DNA markers or to produce transgenic cane sugar in response to signal transduction pathways to environmental stress.42 Plant breeders may develop bioinformatics databases to design hybridization within or between cultivars/varieties for the requirement of the breeding programs to mitigate stress using micropropagation techniques and molecular and gene transformation strategies for improved sugar cane breeding/crop improvement. Bioenergy can be produced in the different ways. They are starch, sugar, and oil from food and other grains and juice of sugar cane (1G, generation biofuels), lignocellulosic biomass from sugar cane bagasse, wood and straw or other related biomass (2G), and algae (3G). Currently, bioethanol is the most common biofuel produced globally.43,44 Molecular studies have been explored for better understanding of genes, proteins, and metabolites in sugar cane for developing knowledge-based strategies, as shown in Figure 1.

Figure 1.

Figure 1

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Schematic diagram summarizing biotechnological interventions to improve sugar cane crop and enhanced sugar/biofuel production.

2. Chromosome, Genomic/Transcriptomic Information, and Databases

A complete census of chromosomal numbers has been attempted with sugar cane.25,45 Much of the research indicated that there is significant variation in the number of chromosomes based on this plant’s geographic location, as shown in Figure 2.

Figure 2.

Figure 2

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Distribution of chromosome numbers among sugar cane varieties based on their geographic origin.46

Sugar cane is an excellent system for studying the evolutionary patterns of chromosome number and genome size evolution among monocots because this group has an unusually high diversity of chromosome47,48 numbers (n = 20–131). The species are perennial and distributed in the tropical ecosystem worldwide19 to adapt under a tropical environment with C4 photosynthesis,49 creating a more suitable crop under climate change conditions with ease of reproduction/hybridization of the different species among the Saccharum genus for creating new traits.45,50 Sugar cane sequencing data are now freely available, which enhance the understanding of genetic and regulatory activities of genes linked with agronomically significant features. The size of the sugar cane genome (nuclear DNA amounts) differs greatly due to varying ploidy levels in various Saccharum spp. It is challenging to study the complex sugar cane genome due to the fact that there are 8–12 alleles in the euploid and aneuploid sugar cane genomes. The genome size ranges from 7.50 to 8.55 Gb with an average length of 7.88 Gb (S. officinarum), 7.65–11.78 Gb of S. robustum, and 3.36–12.64 Gb of S. spontaneum.51,52 Sugar cane Genome Sequencing Initiative (SUGESI) created the first reference genome. Since then, various databases have been accessible for sugar cane genome sequence data, each with its own set of information and tools for interpreting genomic resources and analysis.53 NCBI is a web resource that collects genomic data from many plant species. It also provides access to the Basic Local Alignment Search Tool (BLAST) for determining the index of similarity of the query sequence with the sugar cane genome database under accession number QVOL00000000. Tripal database infrastructure is also included. It was created by CIRAD and is backed up by the South Green Bioinformatics platform. The monoploid reference genome sequence produced from the R570 cultivar is now available under the accession number ERZ654945.

3. Roles of Genomic Studies on Sugar Cane Plants during Environmental Stress

With the completion of the sugar cane genome sequence and the availability of its database, sugar cane breeding may enter into the “genomic” age. Genome-based identification and use gradually evolved into the primary methodologies for determining gene functions. Quantitative trait locus (QTL) mapping is a statistical-analysis-based technique for determining a genetic region in complex features by combining phenotypic data with genotypic data in a population. Several QTL statistical models have been developed, including standard interval mapping (SIM) and multiple imputations (MIPs), which are used when a single QTL is unlinked, and composite interval mapping (CIM), which is designed to map the genetic linkage for both linked and unlinked QTLs/genes on the chromosome. The performance of these approaches is judged using the estimated logarithms-of-odds scores, and QTLs are normally regarded as significant if they are greater than the threshold score of 3.0. It is beneficial to have open access to reference genomes. The presence of open access to reference genomes benefits by providing genetic information on the genes that cause QTLs.50,54,55

A balanced population with known recombination is required for QTL mapping. Following that, linkage mapping may be used to infer a statistical correlation between phenotypic and genotypic data. The location of a QTL may be found by looking for allelic variants of a genetically linked molecular marker that have a significant effect on a quantitative characteristic in the population being examined. The identification of genomic sites aids in the identification of responsible genes and the development of diagnostic tests. The linkage or QTL mapping approach is frequently used in sugar cane.54 The ability to find QTLs that influence target attributes in a specific population have been demonstrated.55,56 Several populations of sugar cane have been developed and used for QTL studies using genetic markers, such as restriction fragment length polymorphism (RFLPs), single sequence repeats (SSRs), and single nucleotide polymorphisms (SNPs). To find grain-yield-related QTLs, a population of 285F1 lines of sugar cane produced from a hybrid between YT93-159 and ROC22 parents was employed, and a total of six sugar cane leaf blight (SLB) QTLs were mapped.57 Another mapping of a population of 169 lines was developed from a cross between K 93-207 and an MPT 97-1 using 180 amplified fragment length polymorphism (AFLP) markers to map the fiber content of sugar cane on 30 QTL locations.58 Five QTLs linked with fiber content were identified by mapping 142 progenies of self-pollinating LCP 85-384 cultivar using NGS to greatly increase SNP density, allowing researchers to find QTLs for smut disease tolerance with increased precision.56 A population of 192 F1 sugar cane lines produced from a cross between two contrasting smut resistant was used to discover these lines.

QTL mapping necessitates the use of genetically different biparental segregating populations, and the variety of the populations may have an impact on the identified QTLs. The constraints of QTL analysis can be overcome by employing a genome-wide association study (GWAS), which uses naturally diverse populations to narrow down possible genomic areas based on linkage disequilibrium. GWAS interprets the connections of each marker and trait of interest using individuals from a varied population (Figure 3). The control of false positives, which can occur due to population structure and family relatedness, is a severe issue in this methodology. False positives are frequently reduced using structural and kinship factors in mixed linear models. These mixed-model-based approaches are single-locus models, resulting in false negatives. With the rapid development and availability of sequencing technologies, GWAS is currently a widely used approach for identifying the loci underlying natural variability in sugar cane. In GWAS, the population is genotyped once, and then it can be used repeatedly to map different traits using new phenotypic data. Because of population dynamics and genetic linkages, GWAS has a high rate of false positives. GWAS studies in sugar cane have been undertaken for more than a decade. The recently created 100K59 and 345K60 SNP arrays have significantly improved the GWAS and QTL mapping efficiency for detecting novel QTLs/genes in sugar cane.

Figure 3.

Figure 3

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Diagram explaining the process of genome-based molecular breeding. GP, germplasm; D, diversity of the germplasm; HGS, whole genome sequencing technology; MAS, marker-assisted selection; GWAS, genome-wide association study; GE, genomic selection and genome editing

For example, gene targets for yellow leaf virus resistance, which is an essential agronomic feature, identified 18 QTLs using the 100K SNP array.57 The combination of more than two mapping populations has not yet been used in sugar cane. Still, it is an efficient approach that represents a step ahead in genetic and candidate gene identification (Figure 3). Genome selection/editing (GE) is a novel approach for selecting individuals that have the ability to speed up genetic grains of complex traits in conventional breeding programs. GE exploits the entire DNA marker information by simultaneously accounting the effect of each marker across the whole genome to predict the genetic value of individuals.61

4. Influence of Transcriptomic Studies on Sugar Cane Development and Productivity under Unfavorable Environmental Conditions

A wide range of genes presented in sugar cane crop under unfavorable environmental conditions has been discovered through molecular analysis.61,62 In silico methods, such as probe hybridization arrays, expressed sequence tags (ESTs), or known genes from other allied crops are used in transcriptomic studies to provide the appropriate gene data. The Brazilian sugar cane EST database is one of the largest, with approximately 238,000 ESTs obtained from 26 different cDNA libraries constructed from a wide range of Brazilian plant varieties using various tissues.63 However, the lack of a complete and accurate sugar cane genome poses a challenge to the transcriptome database prediction and application of genes.64 Therefore, due to the maximum similarity in the genetic regions between the genome of sugar cane and sorghum plants, the Sorghum bicolor reference genome is widely used in transcriptomic experiments.65,66 Assessing the transcriptomic effects of stress on sugar cane crops may provide insights into defensive mechanisms and potential molecular functions to produce stress-resistant plant varieties (Figure 1). The impact of transcriptomic factors (TFs), such as WRKY, MYB, bZIP, AP2/DREBP, and zinc-finger-like proteins, serving as regulatory agents of metabolic pathways responsible for plant defense mechanisms under unfavorable atmospheric variables, has been extensively studied.67 Environmental stress factors negatively affect plant development and yield production in sugar cane plants globally.7 The transcriptome profiles of sugar cane drought-tolerant and susceptible cultivars during a water deficit use the Illumina HiScanSQ system and HiSeq 2500 platforms.68 The main enzyme for flavonoid biosynthesis is the multiple genes, such as ascorbate peroxidase (APx), MYB, and E3 SUMO-protein ligase SIZ2, and the main enzyme for flavonoid biosynthesis, i.e., coenzyme ligase and aquaporin, is induced in stress-tolerant cultivars. These genes/TFs are essential in stress resistance mechanisms.68−70

The genes responsible for ABA in drought and temperature stress conditions were also enhanced. da Silva et al.71 observed similar research findings using HT-SuperSAGE methods to assess different water deficit tolerance and sensitive cultivars. The 9831 induced unitag genes found in the roots of resistance cultivars were regulated differently in sensitive cultivars after being stressed by a lack of sufficient irrigation water. In the metabolic process of sugar cane plants, various stress–response genes play a major role, such as attenuation of ethylene stress, root growth, degradation of protein, oxidative detoxification, synthesis of fatty acid, transport of amino acids, carbohydrate metabolism, and pentose phosphate pathway.71 An experiment on Saccharum narenga (wild-type) subjected to a water deficit observed 3389 differentially expressed genes (DEGs) of up- and down-regulation. DEGs are also associated with the metabolic pathways, with the blue light response being a single transduction of plant hormones.72

Polyamine oxidase, cytochrome c oxidase, S-adenosylmethionine (SAM) decarboxylase, and thioredoxin encoding genes have been studied in sugar cane crops during unfavorable conditions and can help to alleviate stress.42,62 The gene expression encoding PP2C, such as protein phosphatase, S-adenosylmethionine decarboxylase, and two delta-12 oleate desaturases, was induced by abscisic acid (ABA) and water stress. SodERF3 is an ethylene-responsive factor in sugar cane caused by ABA and water deficit conditions and may be linked to stress tolerance mechanisms. Changes in gene expression can protect cellular adaptation to drought, and gene expression profiles reveal the complexities of defense mechanisms.61,73 Microarrays are a well-known tool for determining differentially expressed genes because of their high-throughput capability, which allows the study of several genes simultaneously. A total of 15,593 sugar cane expression genes were found, and only 1501 were differentially expressed genes during stress conditions.61 Various studies have shown functional annotation analyses of genes that are differentially expressed under stressed conditions.74

During cold stress, differential gene expression profiling was performed on S. spontaneum with a transcriptomic technique. The DEG analysis found 5840 genes (up-regulated 2538 and down-regulated 3302 genes) under low temperature. Numerous cold-sensitive genes are linked with various metabolic pathways.75 The effect of the transcriptome profile on sugar cane during low potassium (K) and nitrogen (N) application was examined by Zeng et al.74 and Yang et al.76 Proteins associated with cold and freezing resistance stress were discovered in the expression profiles of chilling inducible genes. For example, one sugar cane EST encoding a putative xanthine dehydrogenase (XDH) was significantly induced after freezing exposure.77,78 The 3575 ESTs found 165 differentially expressed genes in sugar cane plants with stress tolerance, suggesting that a large number of genes are linked to stress tolerance.79 The ESTs can be divided into two groups based on species/varieties: two small groups of ESTs from S. arundinaceum and S. officinarum and an extra-wide group of ESTs derived from Saccharum spp. hybrids, the most advanced sugar cane varieties. Xanthine dehydrogenase (XDH) is a gene that encodes a putative NAD-dependent dehydrogenase80 that has been linked to oxidative stress in the subjective defensive system due to freezing conditions.77 The transcriptomic studies on sugar cane plants have been implemented effectively with advanced molecular technologies, i.e., cDNA microarrays, Roche/454 and Illumina/Solexa, RNA-seq, qPCR, and microscopy, for assessing profiles of expression of genes from cells/tissues and their impacts on structural and functional variations during major development of sugar cane.41,81 The functional changes and annotation of genes involved in major agronomic parameters are more important and helpful in sugar cane varieties that improve plant productivity. Transcriptomic studies have been implemented to explain the gene expression profiles and validate expression patterns.82 Various genes associated with cellulose and lignin biosynthesis, leaf abscission, maturation, and leaf gas exchange have been confirmed in developmental growth and physiological capacity responses.11,61,83,84 Transcriptomic studies have been used in recent development to assess genes described with the traits of interest, such as sugar content and environmental stress avoidance, to improve crop performance (Figure 1).

5. Impact of Proteomics Studies on Sugar Cane Plant Development and Productivity during Environmental Stress

In addition, transcriptomic and proteomics techniques also provide updated insights into complex biological mechanisms.40,85 Therefore, to study biological phenomena, the functions/mechanisms for protein quantification and their post-translational derivatives are essential. While the genome is stagnant, an individual’s proteome dynamically responds to abiotic stress and intracellular metabolic conditions through various levels of expression and post-translational changes such as glycosylation, phosphorylation, methylation, acetylation, etc., further enhancing proteome complexity.40 In sugar cane crops subjected to environmental variables, various protein isolation and quantitation techniques, such as two-dimensional electrophoresis (2-DE), mass spectrometry (MS), and matrix-assisted laser desorption/ionization-time-of-flight mass spectrometry, are used to assess the protein levels of differential and relative expression.40 Also, isobaric tags for relative and absolute quantification (iTRAQ) are key quantitative techniques used in various plant proteomics studies.86

Several proteomics studies have been applied to gel-based or gel-free methods during unfavorable stress conditions in the cane crop. The morphophysiological state and metabolic development of sugar cane are directly or indirectly linked with various stressors.40 Abiotic stress is considered to be multidimensional as it affects innumerable metabolic and cellular processes in crop plants, leading to productivity loss.87 One of the major metabolic processes is the variation in protein synthesis/degradation affecting stress prevention. Proteomics-based demonstrations of stress-tolerant sugar cane functions and pathways have been carried out. 2-DE coupled with LC-ESI-IT-MS/MS/MS was used to isolate and identify specific photosynthetic pathway-related proteins and antioxidative destruction-related enzymes.88 According to Khueychai et al.,87 various proteins responded to water stress in stress-tolerant and sensitive varieties by 2-DE coupled with LC-MS/MS techniques. Different proteins, such as fructose 1,6-bisphosphate aldolase, germin-like protein, glyceraldehyde-3-phosphate dehydrogenase, and heat-shock protein (HSP), were differentially expressed against normal and saline stress in Saccharum spp. by 2-DE and MS methods.89 HSPs play a major role in mitigating environmental stress tolerance in plants.10

Proteomics techniques have also been used to present proteome regulation in sugar cane developmental processes, as well as proteome profiling in various sugar cane plant sections. It is essential for sugar cane growth and development processes to obtain full proteomic coverage. Proteomics analysis between putrescine and normal conditions found somatic embryogenesis-related DEPs, i.e., arabinogalactan proteins, peroxidases, HSPs, glutathione-S-transferases, late embryogenesis abundant proteins, and 14–3–3 proteins, play a major role in cell protection during stressful environmental conditions.90 The cell wall proteomics of young and photosynthetically mature sugar cane leaves and stems revealed that they had the maximum rate of lipid metabolism of all species and enriched 277 sugar-cane-labeled cell wall proteins (CWPs). Molecular and gene transformation technologies were used to develop genetically modified sugar cane crop varieties.44,91

6. Manipulating the Sugar Cane Genome by Advanced Molecular Approaches

Genome engineering is a routine in many research laboratories, and more than 190 mha of the cultivable land is under biotech crops worldwide.92 Different biological and physical methods have been used for sugar cane genome engineering. They include Agrobacterium-mediated gene transfer, particle bombardment, polyethylene glycol, and electroporation with different success rates. Agrobacterium and a biolistic gun are the most successful methods with higher transformation efficiency.93 Though sugar cane transformation is impeded by the complexity of the genome and the long cycle of vegetative propagation, efforts have been made to tame its genome.94 The first transformation event was attained with a biolistic gun using npt-II gene under the Emu promoter.95,96

Agrobacterium-mediated transformation is carried out with Agrobacterium tumefaciens, i.e., Gram-negative bacteria present in soil with T-DNA present in Ti (tumor-inducing) plasmid to infect plant cells and integration into the plant genome.70 This natural DNA transfer system has been used as the vector for plant transformation.97 Due to the availability of the highly virulent Agrobacterium strain, stable and reliable in vitro plant regeneration system, and vir-activating chemicals, this transformation method has various benefits for sugar cane transformation. For sugar cane, protocols for callus culture, vegetative propagation, and tissue culture from stem cutting, shoot tips, or meristem have been established.98 Better growth, sprouting, cane yield, and sugar contents and decreased diseases were observed in sugar cane developed from tissue culture and micropropagation.99,100 Mustafa and Khan101 reported the sugar cane plastid transformation for the first time.

6.1. Genome Editing

Genome editing is the modification of DNA via the deletion/insertion of DNA in an organism. CRISPR/Cas (clustered regularly interspaced short palindromic repeats), TALEN (transcription activator-like effector nuclease), meganucleases, and ZFN (zinc finger nucleases) are genome editing technologies.102 Though all four genome editing approaches are used, CRISPR/Cas is widely used due to having some advantages; CRISPR/Cas may recognize DNA/RNA-specific sequence, whereas all other techniques are based on protein recognition. The second advantage of CRISPR is multiplexing, in which multiple genes may be edited simultaneously. The third advantage of CRISPR over TALEN and ZFN is that plant transformation and vector construction are efficient and straightforward, while TALEN and ZFNs perform their function as dimers, so they have many complications.103

Being a complex polyploid crop with 8–12 copies of homologous genes and 10 GB genome size makes genome editing much more difficult in sugar cane.104 Transgene silencing at transcriptional and post-transcriptional levels is a big drawback in the molecular improvement of sugar cane.105 Genome editing by CRISPR/Cas may also have off-target effects, i.e., cutting-off off-target sequences with a gRNA/Cas protein along with target sequences, which can be minimized using several specific promoters with truncated gRNA/Cas protein complexes and further eliminated using modified variants of CRISPR-associated nucleases.106,107 In spite of several challenges, soon CRISPR/Cas will be a desirable tool for genome editing in sugar cane and other polyploid crops. Functional genomics resources are a critical requirement of genome editing, and it should be available to design precise gRNA to target any gene for which the function is known. To design a specific gRNA, sequence variation between different allelic forms of polyploidy crops, i.e., sugar cane, should be known. The whole sugar cane genome sequence is not interpreted yet, so genomics resources are limited in spite of some EST and transcriptomics data. Moreover, the function of more than 10,000 genes is not yet known.108

Some studies reported sugar cane genome editing by transcription activator-like effector nuclease (TALEN). Genome editing in a wide variety of plants, e.g., tomato, flaxseed, sugar cane, wheat, barley, soybean, maize, rice, Brachypodium, Nicotiana, and Arabidopsis have been carried out by TALEN.109,110 TALEN was first used in rice to silence OsSWEET14, a bacterial blight susceptible gene, and the resultant rice plants were resistant to bacterial blight disease.111 The TALEN-mediated genome editing approach in sugar cane has improved saccharification efficiency and cell wall composition. For this purpose, a conserved region of the caffeic acid O-methyltransferase (COMT) gene was targeted to improve lignin biosynthesis in sugar cane for biomass production.112

7. Transformation Approaches for Abiotic and Biotic Stress Tolerance

Plant genetic engineering may be used for sugar cane genetic improvement by increasing resistance to biotic and abiotic stress for crop productivity, as they impair metabolism, development, and growth,113 viz., drought, salinity, heat, cold, diseases caused by virus, bacteria, fungi, and insects. To combat this stress, several defense responses have been stimulated by activating the synthesis of proteins involved in crucial pathways like LEA (late-embryogenesis abundant, antioxidant enzymes, protease inhibitor, and transcription factors, i.e., ERF/AP2, MYB, NAC, and WRKY).114,115

Sugar cane crops face drought stress more commonly, affecting their yield, and their production needs substantial irrigation to grow on land with restricted water supply.116−118 Several studies reported the transformation of vacuolar pyrophosphatase (AVP1) and trehalose synthase genes into sugar cane to enhance drought resistance.119 Expression profiling was used to identify genes expressed under abiotic stress. Changes in gene expression were evaluated by growing wild-type cultivars under salinity, drought, and cold stress. Noteworthy variations in gene expression of GolS (glactinol synthase), P5CS (pyrroline-5-carboxylase synthase), ERD4 (early responsive dehydration protein-4), and LEA3 (late-embryogenesis abundant protein-3) were observed. Up-regulation in GolS, P5CS, LEA4, and ERD4 was observed under salinity, cold, and drought stress, respectively. Heringer et al.90 reported the up-regulation of ERD4 and P5CS by transferring the Arabidopsis CBF4 gene in sugar cane.120 ScMYB (sugar cane transcription factor gene) and its forms, i.e., ScMYB2S1 and ScMYB2S2, activate the ABA signaling pathway, which plays an important role in drought tolerance.70 Enhanced drought tolerance in sugar cane was observed by overexpression of PDH45 from Pisum sativum and EaDREB2 from E. arundinaceus.10 Similarly, drought and salinity tolerance was enhanced by transferring the PDH45 gene under the PortUbi2.3 promoter in sugar cane.121

The positive role of proline accumulation in abiotic stress tolerance was reported in rice, onion, and soybean,122,123 and increased proline contents were reported in sugar cane under salt124 and drought stress.13,117,125 After a 25% increase in proline content, better salt stress resistance was observed by transferring the Vigna aconitifoliaP5C5 gene to sugar cane plants.126 Moreover, sugar cane transformation with the AtBI-1 (Bax inhibitor from Arabidopsis thaliana) gene effectively increased drought tolerance.127 The differential expression of genes was involved in phytochrome signaling, calcium signaling, biosynthesis of lipid, sugar, pectin, and lignin, MAP kinase, and CBF6 (cold-responsive gene) under cold stress in IND00-1037 cultivar of S. spontaneum.75 Some Ca2+ and methylene metabolic pathways were reported to be involved in the activation of genes with tolerance against potassium deficiency.74

Sugar cane was genetically modified by transferring cry1Aa3,128 cry1Ac,129 cry1Ab,130,131 and cry1A132 from Bacillus thuringiensis to enhance resistance against insects and borers. Zhangsun et al.133 observed the development of insect-resistant sugar cane genotype by transferring the snowdrop lectin (Galanthusnivalis agglutinin, GNA) gene under the control of rice sucrose synthase promoter through Agrobacterium-mediated transformation. The most common trait introduced in sugar cane by genetic transformation is herbicide resistance.134−136 Parvaiz et al.137 reported the increased resistance in sugar cane against red rot by overexpression of SUGARWIN genes under the control of a ubiquitin promoter. Enhanced resistance in sugar cane against Colletotrichum infection was observed by expression of β-1,3- glucanase gene from Trichoderma spp.138−140 Some studies have been performed to increase the sucrose content in sugar cane by genetic transformation of sucrose phosphate synthase (SPS) and polyphenol oxidase (PPO) genes.141 Botha et al.142 reported the development of transgenic sugar cane with reduced soluble acid invertase (SAI) gene activity.

8. Conclusion

Sugar cane productivity has been directly or indirectly affected by adverse climatic variables. Therefore, agriscientists and policy makers must work closely to mitigate the harmful effects of various stress associated with sugar cane cultivation to enhance plant productivity by developing suitable new sugar cane varieties/cultivars through modern breeding programs linked with molecular biology. Advanced techniques may also be used to understand the changes that occur in sugar cane crop exposed to stress to unlayer the molecular strategies of proteogenomics for sustainable crop improvement to achieve the global target of sugar/carbon currency in times to come.

Acknowledgments

The authors would like to thank the Guangxi Academy of Agricultural Sciences, Nanning, Guangxi, China, for providing the necessary facilities for this study.

Author Contributions

Conceptualization, K.K.V., and Y.R.L.; validation, K.K.V., X.P.S., and Y.R.L.; resources, K.K.V., X.P.S., H.R.H., and L.X.; data curation, K.K.V., G.Y., H.D.D., A.P., and G.M.; writing—original draft preparation, K.K.V.; writing—review and editing, M.S., and Y.R.L.; visualization, X.P.S. and Y.R.L.; supervision, X.P.S. and Y.R.L.; project administration, X.P.S. and Y.R.L.; funding acquisition, X.P.S. and Y.R.L. All authors approved the article for publication.

This research was financially supported by the Guangxi Innovation Teams of Modern Agriculture Technology (nycytxgxcxtd-2021-03), Youth Program of National Natural Science Foundation of China (31901594), The National Natural Science Foundation of China (31760415), Guangxi Natural Science Foundation (2021GXNSFAA220022), Fund of Guangxi Academy of Agricultural Sciences (2021YT011) and Guangxi Key Laboratory of Sugar cane Genetic Improvement Project (21-238-16-K-04-02).

The authors declare no competing financial interest.

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